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Description

Statistical Inference and Related Topics, Volume 2 presents the proceedings of the Summer Research Institute on Statistical Inference for Stochastic Processes, held in Bloomingdale, Indiana on July 31 to August 9, 1975. This book focuses on the theory of statistical inference for stochastic processes.

Organized into 15 chapters, this volume begins with an overview of the case of continuous distributions with one real parameter. This text then reviews some results for multidimensional empirical processes and Brownian sheets when they are indexed by families of sets. Other chapters consider a class of cubic spline estimators of probability density functions over a finite interval. This book discusses as well the method to construct nonelimination type sequential procedures to select a subset containing all the superior populations. The final chapter deals with Markov sequences, which are among the most interesting available for study with a rich theory and varied applications.

This book is a valuable resource for graduate students and research workers.

Table of Contents

List of Contributors
Preface
Contents of Volume 1
On Asymptotically Complete Classes
Multidimensional Empirical Processes: Some Comments
Monte Carlo of Two-Dimensional Brownian Sheets
Asymptotic Results on a Spline Estimate of a Probability Density
A Bernstein Polynomial Approach to Density Function Estimation
On Some Parametric and Nonparametric Sequential Subset Selection Procedures
Rank Statistics, Martingales and Limit Theorems
Optimal Stopping Rules for Xn/n and Sn/n
A Survey of the Sn/n Problem
Some Non-Standard Problems of Inference in Stochastic Processes
Asymptotic Properties of Maximum Probability Estimates in the IID Case
A Stochastic Process Under the Influence of Another Arising in the Theory of Epidemics
Inference in a Distribution Related to a 2 x 2 Markov Chain
Statistical Inference for Some Special Families of Stochastic Processes
Record Values in Markov Sequences

About the Editor

Madan Lal Puri

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